Use the code below to re-define the standardize() function and to create a vector with standardized numbers.
standardize <- function (x) {
(x - mean(x, na.rm = TRUE)) / sd(x, na.rm = TRUE)
}
standardized_vector <-
standardize(sample(1:100, 30))
for()-loop, loop through each element of the vector, add the number pi, and print the result.
pi. Just type pi and you’ll receive 3.141593. You need to wrap what the function does within the print() function.
for (number in standardized_vector) {
print(number + pi)
}
## [1] 2.03279
## [1] 1.781107
## [1] 2.997574
## [1] 4.339883
## [1] 2.871733
## [1] 3.962358
## [1] 2.242526
## [1] 2.955627
## [1] 1.906948
## [1] 3.878464
## [1] 5.598297
## [1] 4.130147
## [1] 1.697213
## [1] 3.081468
## [1] 3.920411
## [1] 2.284473
## [1] 2.703944
## [1] 3.626781
## [1] 2.116684
## [1] 2.32642
## [1] 4.004306
## [1] 2.494208
## [1] 3.039521
## [1] 4.591566
## [1] 2.200578
## [1] 3.333151
## [1] 2.158631
## [1] 4.759354
## [1] 3.542887
## [1] 3.668728
sapply() function here.
print() function anymore.
sapply(standardized_vector, function (number) {
number + pi
})
## [1] 2.032790 1.781107 2.997574 4.339883 2.871733 3.962358 2.242526 2.955627 1.906948 3.878464 5.598297 4.130147 1.697213 3.081468
## [15] 3.920411 2.284473 2.703944 3.626781 2.116684 2.326420 4.004306 2.494208 3.039521 4.591566 2.200578 3.333151 2.158631 4.759354
## [29] 3.542887 3.668728
lapply() or map() from the purrr package.
library(purrr)
lapply(standardized_vector, function (number) {
number + pi
})
## [[1]]
## [1] 2.03279
##
## [[2]]
## [1] 1.781107
##
## [[3]]
## [1] 2.997574
##
## [[4]]
## [1] 4.339883
##
## [[5]]
## [1] 2.871733
##
## [[6]]
## [1] 3.962358
##
## [[7]]
## [1] 2.242526
##
## [[8]]
## [1] 2.955627
##
## [[9]]
## [1] 1.906948
##
## [[10]]
## [1] 3.878464
##
## [[11]]
## [1] 5.598297
##
## [[12]]
## [1] 4.130147
##
## [[13]]
## [1] 1.697213
##
## [[14]]
## [1] 3.081468
##
## [[15]]
## [1] 3.920411
##
## [[16]]
## [1] 2.284473
##
## [[17]]
## [1] 2.703944
##
## [[18]]
## [1] 3.626781
##
## [[19]]
## [1] 2.116684
##
## [[20]]
## [1] 2.32642
##
## [[21]]
## [1] 4.004306
##
## [[22]]
## [1] 2.494208
##
## [[23]]
## [1] 3.039521
##
## [[24]]
## [1] 4.591566
##
## [[25]]
## [1] 2.200578
##
## [[26]]
## [1] 3.333151
##
## [[27]]
## [1] 2.158631
##
## [[28]]
## [1] 4.759354
##
## [[29]]
## [1] 3.542887
##
## [[30]]
## [1] 3.668728
standardized_vector %>%
map(~.x + pi)
## [[1]]
## [1] 2.03279
##
## [[2]]
## [1] 1.781107
##
## [[3]]
## [1] 2.997574
##
## [[4]]
## [1] 4.339883
##
## [[5]]
## [1] 2.871733
##
## [[6]]
## [1] 3.962358
##
## [[7]]
## [1] 2.242526
##
## [[8]]
## [1] 2.955627
##
## [[9]]
## [1] 1.906948
##
## [[10]]
## [1] 3.878464
##
## [[11]]
## [1] 5.598297
##
## [[12]]
## [1] 4.130147
##
## [[13]]
## [1] 1.697213
##
## [[14]]
## [1] 3.081468
##
## [[15]]
## [1] 3.920411
##
## [[16]]
## [1] 2.284473
##
## [[17]]
## [1] 2.703944
##
## [[18]]
## [1] 3.626781
##
## [[19]]
## [1] 2.116684
##
## [[20]]
## [1] 2.32642
##
## [[21]]
## [1] 4.004306
##
## [[22]]
## [1] 2.494208
##
## [[23]]
## [1] 3.039521
##
## [[24]]
## [1] 4.591566
##
## [[25]]
## [1] 2.200578
##
## [[26]]
## [1] 3.333151
##
## [[27]]
## [1] 2.158631
##
## [[28]]
## [1] 4.759354
##
## [[29]]
## [1] 3.542887
##
## [[30]]
## [1] 3.668728